Intelligent sensing for robotic re-manufacturing in aerospace — An industry 4.0 design based prototype

Abstract

Abstract-Emergingthrough an industry-academia collaboration between the University of Sheffield and VBC Instrument Engineering Ltd, a proposed robotic solution for remanufacturing of jet engine compressor blades is under ongoing development, producing the first tangible results for evaluation. Having successfully overcome concept adaptation, funding mechanisms, design processes, with research and development trials, the stage of concept optimization and end-user application has commenced. A variety of new challenges is emerging, with multiple parameters requiring control and intelligence. An interlinked collaboration between operational controllers, Quality Assurance (QA) and Quality Control (QC) systems, databases, safety and monitoring systems, is creating a complex network, transforming the traditional manual re-manufacturing method to an advanced intelligent modern smart-factory. Incorporating machine vision systems for characterization, inspection and fault detection, alongside advanced real-time sensor data acquisition for monitoring and evaluating the welding process, a huge amount of valuable industrial data is produced. Information regarding each individual blade is combined with data acquired from the system, embedding data analytics and the concept of "Internet of Things" (IoT) into the aerospace re-manufacturing industry. The aim of this paper is to give a first insight into the challenges of the development of an Industry 4.0 prototype system and an evaluation of first results of the operational prototype.

Assessing relations between Circular Economy and Industry 4.0: a systematic literature review

“…Again, the IoT is suitable for developing new services and CBMs (Alcayaga and Hansen 2017). In a few cases, the optimisation of SCM performance (J. Xu 2009) and remanufacturing processes (French, Benakis, and Marin-Reyes 2017) were considered by experts.…”

“…x (Miranda et al 2017) x (Rødseth, Schjølberg, and Marhaug 2017) x (Sharpe et al 2018) x (Thoben, Wiesner, and Wuest 2017) x (Yu, Xu, and Lu 2015) x T o t a l 7 7 1 1 x (Esmaeilian et al 2018) x (French, Benakis, and Marin-Reyes 2017) x x (Holligan, Hargaden, and Papakostas 2017) x (Mashhadi and Behdad 2018) x (Menon, Kärkkäinen, and Gupta 2016) x (Menon et al 2018) x (Nasiri, Tura, and Ojanen 2017) x (Pacis, Subido Jr., and Bugtai 2017) x (Pistol, Bucea-Manea-Tonis, and Bucea-Manea-Tonis 2017)…”

“…Few works focused on BDA, CPSs, and the IoT. BDA has been exploited for assessing cost reduction strategies through remanufacturing (Ge and Jackson 2014), CPSs for improving current remanufacturing performance (Liu et al 2016), and the IoT for developing innovative ones (French, Benakis, and Marin-Reyes 2017). However, several papers did not consider a specific I4.0 technology.…”

“…Simulation was the prevalent technique, followed by AM, BDA, and the IoT. From one perspective, simulation (in the form of blockchain) was exploited for (i) auditing cooperative CE networks (Alexandris et al 2018), (ii) assessing the impact of business model changes (Simons 2017), for example, through agent-based or multi-method approaches , and (iii) assessing redistributed manufacturing or service-based design (Panarotto, Wall, and Larsson 2017) (French, Benakis, and Marin-Reyes 2017) x (Ge and Jackson 2014) x (Karastoyanov and Karastanev 2018) x (Kuik, Kaihara, and Fujii 2016) x (Lahrour and Brissaud 2018) x (Le, Paris, and Mandil 2017a) x (Le, Paris, and Mandil 2017b) x (Leino, Pekkarinen, and Soukka 2016) x (Liu et al 2016) x (Ruggeri et al 2017) x (Shanshan Yang et al 2018) x (Siddiqi et al 2017) x (Stark et al 2014) x (Tolio et al 2017) x (X. V. x (B. Xu 2016)…”

Integrating Virtual Reality and Digital Twin in Circular Economy Practices: A Laboratory Application Case

“…A CPS was thus developed for the real-time monitoring of CNC machines and the definition of maintenance activities. French et al [40] described the use of robots, BDA, and IoT for improving remanufacturing performances in the aerospace industry. By incorporating machine vision systems for characterization, inspection, and fault detection, alongside advanced real-time sensor data acquisition for monitoring and evaluating the welding process, manual remanufacturing can become a smart process.…”